MIT License

grant

OME (Open Microscopy Environment) develops open-source software and data format standards for the storage and manipulation of biological light microscopy data. A joint project between universities, research establishments and industry in Europe and the USA, OME has over 20 active researchers with strong links to the microscopy community. Funded by private and public research grants, OME has been a major force on the international microscopy stage since 2000.

GNU General Public License v2.0

openmicroscopy

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

Apache License 2.0

Auto_ViML

Grant superuser permission, then do nothing

sudont

The Mohawk College MARC-HI/MEDIC Client Registry Reference Implementation represents the prototype Client Registry (Enterprise Master Patient Index - EMPI) developed under our Natural Sciences and Engineering Research Council of Canada (NSERC) grant to build a test version of the pan-Canadian Electronic Health Record System blueprint as prescribed by Canada Health Infoway.

Other

client-registry

Simple Go proxy for injecting Web Monetization meta tags. Done as part of the Dev "Grant For The Web" Hackathon

web-monetization-proxy


Description


This is macOS version of the iOS app waifu2x.This app can scale and/or denoise images, GIFs and videos using various advanced on-device AI algorithms. Note that this app is not affiliated with the original waifu2x project.Privacy is one of the top priorities of this app. Your images and videos will never leave your device to be processed. Additionally, we don't collect any personal information because there are no ADs even if you only use free models. Therefore, if you encounter any problems, please send us a feedback email or create a GitHub issue so that we can work together to fix them.Try additional models and custom models on your own images for free before you purchase!macOS exclusive features:1. Command line interface (CLI) support.2. Advanced video processing via CLI.3. Accelerate batch processing using multiple GPUs and ANE in parallel (advanced mode required). All models except for CUnet are supported.Highlight features:1. Unlimited number of imported images, GIFs and videos.2. Supports both SRCNN and CUnet models from the original waifu2x project.3. Supports Real-ESRGAN models for both illustrations and photos.4. Supports Real-CUGAN models for anime illustrations. Also supports customizable intensity.5. Supports Anime4K models for anime videos.6. Supports custom Core ML models. Import any model to process images for your specific needs.7. Custom scale modes. You have options to scale images up to 128x, 1.5x, fixed size and more.8. Supports multiple ways of importing images and videos: the album, files, folders, drag and drop, other apps, Shortcuts.9. Supports images with alpha channel.10. Multiple output formats: PNG, JPEG, HEIF, WebP, MP4, MOV, GIF, APNG, AWebP.11. Multiple processing backends. You can choose between highest quality or highest speed.12. Write output images and videos directly to an external path (including network drives like SMB).13. End-to-end support for 16-bit color and color spaces. Color accuracy will not be compromised after processing.14. Highly optimized RAM usage. You can easily produce images that don't even fit inside your device RAM.15. Supports deleting or replacing original images and videos if they come from the album.16. Supports downscaling images before processing, which is useful while processing some photos.SRCNN and CUnet models are converted from waifu2x-caffe.All the models are running on device, so it doesn't need to upload images or videos to any server.Source code of core function is available on GitHub:https://github.com/imxieyi/waifu2x-iosUsage of images in screenshots is granted by the original author Kurumi:https://twitter.com/0115_kurumiThe primary app icon is illustrated by Kapuru:https://twitter.com/KaPuRu_0410


